A comprehensive architecture to support open data access, co-creation, and dissemination

Ojo, Adegboyega; Stasiewicz, Arkadiusz; Porwol, Lukasz; Petta, Andrea; Pirozzi, Donato; Serra, Luigi; Scarano, Vittorio; Vicidomini, Luca

doi:10.1145/3209281.3209411

Cited by 3 publications

(5 citation statements)

References 2 publications

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“…Quality is a dynamic concept but the degree to which data is indeed usable is often considered a factor because usability has such a big impact not only on whether stakeholders use open data as intended but whether the values OGD is intended to promote are realized. Usability has been discussed quite a bit in the literature but mostly from a technical aspect with ease of access and navigation (Cucciniello et al, 2012;Pina et al, 2010;Pina et al, 2007) and quality of data (Bertot et al, 2014;Arrard et al, 2015;Zhu & Freeman, 2019;Ojo et al, 2018;Vetro et al, 2016) being necessary, but still overlooked, conditions of usability.…”

Section: Quality Datamentioning

confidence: 99%

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Whose open data is it anyway? An exploratory study of open government data relevance and implications for democratic inclusion

Schwoerer¹

2022

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Open government data (OGD) is believed to enhance democratic outcomes by empowering citizens with the information necessary to participate in meaningful ways. Nonetheless, questions remain about whether OGD is indeed empowering citizens to participate or if the data that governments publish is more reflective of the interests of non-citizen stakeholders. Using the metadata of 2607 publicly available datasets scraped from New York City’s open data portal, this exploratory study uses qualitative content analysis to identify what types of data are published and what the data say about OGD’s potential as a tool for advancing inclusion in democratic processes. The analysis focused particularly on the datasets’ relevance to five particular stakeholder groups: citizens, private sector firms, nonprofits, researchers, and the city’s internal agencies. Findings showed that non-citizen-relevant datasets not only outnumbered citizen-relevant datasets by a large margin but they were also viewed and downloaded at higher rates too. The implications of this for inclusion in democratic processes are discussed, including power imbalances among OGD user groups, the discretionary power data publishers possess, and, ultimately, whether the types of data cities publish is sufficient for empowering an informed citizenry, as an effective democracy demands.

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Section: Quality Datamentioning

confidence: 99%

“…Previous studies have also emphasized the importance of providing communities with the information they actually care about like data on crime, public health, and the environment (Ojo et al, 2018). Ultimately, the information provided should provide value to its users.…”

Section: Relevant and Useful Datamentioning

confidence: 99%

Whose open data is it anyway? An exploratory study of open government data relevance and implications for democratic inclusion

Schwoerer¹

2022

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“…Determining the optimal radius requires experimentation like a typical model selection problem. This SOM-based relatedness procedure has already been implemented as extensions to instances of the CKAN data platform with very good results [6]. The number of datasets returned is based on the degree of relatedness specified.…”

Section: Computing Dataset Relatedness Using Sommentioning

confidence: 99%

“…The model has been extended to the Dutch Language with equally good results. It is also been used as a basis for identifying datasets that can be merged [6].…”

Section: Computing Dataset Relatedness Using Sommentioning

confidence: 99%

“…Users have no way of discovering how datasets are related or what other datasets could be of interest or potentially valuable to them. Prototypes of next-generation open data platforms are beginning to emerge with features to support the recommendation of datasets [4], social engagement around data [5,6] and automatic extraction of facts from datasets in form data stories that are more meaningful for users [7].…”

Section: Introductionmentioning

confidence: 99%

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Constructing Knowledge Graphs from Data Catalogues

Ojo

Sennaike

2019

Distributed Computing and Internet Technology

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We have witnessed about a decade's effort in opening up government institutions around the world by making data about their services, performance and programmes publicly available on open data portals. While these efforts have yielded some economic and social value particularly in the context of city data ecosystems, there is a general acknowledgment that the promises of open data are far from being realised. A major barrier to better exploitation of open data is the difficulty in finding datasets of interests and those of high value on data portals. This article describes how the implicit relatedness and value of datasets can be revealed by generating a knowledge graph over data catalogues. Specifically, we generate a knowledge graph based on a self-organizing map (SOM) constructed from an open data catalogue. Following this, we show how the generated knowledge graph enables value characterisation based on sociometric profiles of the datasets as well as dataset recommendation.

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